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<div class="title">gicp.hpp</div>  </div>
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> *  Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *  Copyright (c) 2010, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> *  Copyright (c) 2012-, Open Perception, Inc.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> *  All rights reserved.</span></div>
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<div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> *  Redistribution and use in source and binary forms, with or without</span></div>
<div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> *  modification, are permitted provided that the following conditions</span></div>
<div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *  are met:</span></div>
<div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> *   * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *     notice, this list of conditions and the following disclaimer.</span></div>
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<div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="comment"> * $Id$</span></div>
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<div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;<span class="preprocessor">#ifndef PCL_REGISTRATION_IMPL_GICP_HPP_</span></div>
<div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;<span class="preprocessor">#define PCL_REGISTRATION_IMPL_GICP_HPP_</span></div>
<div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160; </div>
<div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;<span class="preprocessor">#include &lt;pcl/registration/boost.h&gt;</span></div>
<div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;<span class="preprocessor">#include &lt;pcl/registration/exceptions.h&gt;</span></div>
<div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160; </div>
<div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00048"></a><span class="lineno"><a class="line" href="classpcl_1_1_generalized_iterative_closest_point.html#a796c0d782df55e6b35f726a5f6b34097">   48</a></span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a796c0d782df55e6b35f726a5f6b34097">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::setInputCloud</a> (</div>
<div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;    <span class="keyword">const</span> <span class="keyword">typename</span> pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::PointCloudSourceConstPtr &amp;cloud)</div>
<div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;{</div>
<div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;  setInputSource (cloud);</div>
<div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;}</div>
<div class="line"><a name="l00053"></a><span class="lineno">   53</span>&#160; </div>
<div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt;</div>
<div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;<span class="keyword">template</span>&lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00057"></a><span class="lineno"><a class="line" href="classpcl_1_1_generalized_iterative_closest_point.html#a4307aa8507e98a86183d3ba4cb5400d0">   57</a></span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a4307aa8507e98a86183d3ba4cb5400d0">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::computeCovariances</a>(<span class="keyword">typename</span> pcl::PointCloud&lt;PointT&gt;::ConstPtr cloud,</div>
<div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;                                                                                    <span class="keyword">const</span> <span class="keyword">typename</span> pcl::search::KdTree&lt;PointT&gt;::Ptr kdtree,</div>
<div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;                                                                                    MatricesVector&amp; cloud_covariances)</div>
<div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;{</div>
<div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;  <span class="keywordflow">if</span> (k_correspondences_ &gt; <span class="keywordtype">int</span> (cloud-&gt;size ()))</div>
<div class="line"><a name="l00062"></a><span class="lineno">   62</span>&#160;  {</div>
<div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;    PCL_ERROR (<span class="stringliteral">&quot;[pcl::GeneralizedIterativeClosestPoint::computeCovariances] Number or points in cloud (%lu) is less than k_correspondences_ (%lu)!\n&quot;</span>, cloud-&gt;size (), k_correspondences_);</div>
<div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;  }</div>
<div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160; </div>
<div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;  Eigen::Vector3d mean;</div>
<div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;  std::vector&lt;int&gt; nn_indecies; nn_indecies.reserve (k_correspondences_);</div>
<div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;  std::vector&lt;float&gt; nn_dist_sq; nn_dist_sq.reserve (k_correspondences_);</div>
<div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160; </div>
<div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;  <span class="comment">// We should never get there but who knows</span></div>
<div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;  <span class="keywordflow">if</span>(cloud_covariances.size () &lt; cloud-&gt;size ())</div>
<div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;    cloud_covariances.resize (cloud-&gt;size ());</div>
<div class="line"><a name="l00074"></a><span class="lineno">   74</span>&#160; </div>
<div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;  <span class="keyword">typename</span> pcl::PointCloud&lt;PointT&gt;::const_iterator points_iterator = cloud-&gt;begin ();</div>
<div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;  MatricesVector::iterator matrices_iterator = cloud_covariances.begin ();</div>
<div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;  <span class="keywordflow">for</span>(;</div>
<div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;      points_iterator != cloud-&gt;end ();</div>
<div class="line"><a name="l00079"></a><span class="lineno">   79</span>&#160;      ++points_iterator, ++matrices_iterator)</div>
<div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;  {</div>
<div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &amp;query_point = *points_iterator;</div>
<div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    Eigen::Matrix3d &amp;cov = *matrices_iterator;</div>
<div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;    <span class="comment">// Zero out the cov and mean</span></div>
<div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    cov.setZero ();</div>
<div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;    mean.setZero ();</div>
<div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160; </div>
<div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    <span class="comment">// Search for the K nearest neighbours</span></div>
<div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    kdtree-&gt;<a class="code" href="classpcl_1_1search_1_1_kd_tree.html#a6be8fe286786c3b1aeda7d5369f9cb3e">nearestKSearch</a>(query_point, k_correspondences_, nn_indecies, nn_dist_sq);</div>
<div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160; </div>
<div class="line"><a name="l00090"></a><span class="lineno">   90</span>&#160;    <span class="comment">// Find the covariance matrix</span></div>
<div class="line"><a name="l00091"></a><span class="lineno">   91</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> j = 0; j &lt; k_correspondences_; j++) {</div>
<div class="line"><a name="l00092"></a><span class="lineno">   92</span>&#160;      <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_x_y_z_r_g_b_a.html">PointT</a> &amp;pt = (*cloud)[nn_indecies[j]];</div>
<div class="line"><a name="l00093"></a><span class="lineno">   93</span>&#160; </div>
<div class="line"><a name="l00094"></a><span class="lineno">   94</span>&#160;      mean[0] += pt.x;</div>
<div class="line"><a name="l00095"></a><span class="lineno">   95</span>&#160;      mean[1] += pt.y;</div>
<div class="line"><a name="l00096"></a><span class="lineno">   96</span>&#160;      mean[2] += pt.z;</div>
<div class="line"><a name="l00097"></a><span class="lineno">   97</span>&#160; </div>
<div class="line"><a name="l00098"></a><span class="lineno">   98</span>&#160;      cov(0,0) += pt.x*pt.x;</div>
<div class="line"><a name="l00099"></a><span class="lineno">   99</span>&#160; </div>
<div class="line"><a name="l00100"></a><span class="lineno">  100</span>&#160;      cov(1,0) += pt.y*pt.x;</div>
<div class="line"><a name="l00101"></a><span class="lineno">  101</span>&#160;      cov(1,1) += pt.y*pt.y;</div>
<div class="line"><a name="l00102"></a><span class="lineno">  102</span>&#160; </div>
<div class="line"><a name="l00103"></a><span class="lineno">  103</span>&#160;      cov(2,0) += pt.z*pt.x;</div>
<div class="line"><a name="l00104"></a><span class="lineno">  104</span>&#160;      cov(2,1) += pt.z*pt.y;</div>
<div class="line"><a name="l00105"></a><span class="lineno">  105</span>&#160;      cov(2,2) += pt.z*pt.z;</div>
<div class="line"><a name="l00106"></a><span class="lineno">  106</span>&#160;    }</div>
<div class="line"><a name="l00107"></a><span class="lineno">  107</span>&#160; </div>
<div class="line"><a name="l00108"></a><span class="lineno">  108</span>&#160;    mean /= <span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (k_correspondences_);</div>
<div class="line"><a name="l00109"></a><span class="lineno">  109</span>&#160;    <span class="comment">// Get the actual covariance</span></div>
<div class="line"><a name="l00110"></a><span class="lineno">  110</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k &lt; 3; k++)</div>
<div class="line"><a name="l00111"></a><span class="lineno">  111</span>&#160;      <span class="keywordflow">for</span> (<span class="keywordtype">int</span> l = 0; l &lt;= k; l++)</div>
<div class="line"><a name="l00112"></a><span class="lineno">  112</span>&#160;      {</div>
<div class="line"><a name="l00113"></a><span class="lineno">  113</span>&#160;        cov(k,l) /= <span class="keyword">static_cast&lt;</span><span class="keywordtype">double</span><span class="keyword">&gt;</span> (k_correspondences_);</div>
<div class="line"><a name="l00114"></a><span class="lineno">  114</span>&#160;        cov(k,l) -= mean[k]*mean[l];</div>
<div class="line"><a name="l00115"></a><span class="lineno">  115</span>&#160;        cov(l,k) = cov(k,l);</div>
<div class="line"><a name="l00116"></a><span class="lineno">  116</span>&#160;      }</div>
<div class="line"><a name="l00117"></a><span class="lineno">  117</span>&#160; </div>
<div class="line"><a name="l00118"></a><span class="lineno">  118</span>&#160;    <span class="comment">// Compute the SVD (covariance matrix is symmetric so U = V&#39;)</span></div>
<div class="line"><a name="l00119"></a><span class="lineno">  119</span>&#160;    Eigen::JacobiSVD&lt;Eigen::Matrix3d&gt; svd(cov, Eigen::ComputeFullU);</div>
<div class="line"><a name="l00120"></a><span class="lineno">  120</span>&#160;    cov.setZero ();</div>
<div class="line"><a name="l00121"></a><span class="lineno">  121</span>&#160;    Eigen::Matrix3d U = svd.matrixU ();</div>
<div class="line"><a name="l00122"></a><span class="lineno">  122</span>&#160;    <span class="comment">// Reconstitute the covariance matrix with modified singular values using the column     // vectors in V.</span></div>
<div class="line"><a name="l00123"></a><span class="lineno">  123</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k &lt; 3; k++) {</div>
<div class="line"><a name="l00124"></a><span class="lineno">  124</span>&#160;      Eigen::Vector3d col = U.col(k);</div>
<div class="line"><a name="l00125"></a><span class="lineno">  125</span>&#160;      <span class="keywordtype">double</span> v = 1.; <span class="comment">// biggest 2 singular values replaced by 1</span></div>
<div class="line"><a name="l00126"></a><span class="lineno">  126</span>&#160;      <span class="keywordflow">if</span>(k == 2)   <span class="comment">// smallest singular value replaced by gicp_epsilon</span></div>
<div class="line"><a name="l00127"></a><span class="lineno">  127</span>&#160;        v = gicp_epsilon_;</div>
<div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;      cov+= v * col * col.transpose();</div>
<div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160;    }</div>
<div class="line"><a name="l00130"></a><span class="lineno">  130</span>&#160;  }</div>
<div class="line"><a name="l00131"></a><span class="lineno">  131</span>&#160;}</div>
<div class="line"><a name="l00132"></a><span class="lineno">  132</span>&#160; </div>
<div class="line"><a name="l00134"></a><span class="lineno">  134</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00135"></a><span class="lineno"><a class="line" href="classpcl_1_1_generalized_iterative_closest_point.html#acce93f0ea69ea9d9798529cc6e1083e0">  135</a></span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#acce93f0ea69ea9d9798529cc6e1083e0">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::computeRDerivative</a>(<span class="keyword">const</span> Vector6d &amp;x, <span class="keyword">const</span> Eigen::Matrix3d &amp;R, Vector6d&amp; g)<span class="keyword"> const</span></div>
<div class="line"><a name="l00136"></a><span class="lineno">  136</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00137"></a><span class="lineno">  137</span>&#160;  Eigen::Matrix3d dR_dPhi;</div>
<div class="line"><a name="l00138"></a><span class="lineno">  138</span>&#160;  Eigen::Matrix3d dR_dTheta;</div>
<div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;  Eigen::Matrix3d dR_dPsi;</div>
<div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160; </div>
<div class="line"><a name="l00141"></a><span class="lineno">  141</span>&#160;  <span class="keywordtype">double</span> phi = x[3], theta = x[4], psi = x[5];</div>
<div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160; </div>
<div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;  <span class="keywordtype">double</span> cphi = cos(phi), sphi = sin(phi);</div>
<div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;  <span class="keywordtype">double</span> ctheta = cos(theta), stheta = sin(theta);</div>
<div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;  <span class="keywordtype">double</span> cpsi = cos(psi), spsi = sin(psi);</div>
<div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160; </div>
<div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;  dR_dPhi(0,0) = 0.;</div>
<div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;  dR_dPhi(1,0) = 0.;</div>
<div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;  dR_dPhi(2,0) = 0.;</div>
<div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160; </div>
<div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;  dR_dPhi(0,1) = sphi*spsi + cphi*cpsi*stheta;</div>
<div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;  dR_dPhi(1,1) = -cpsi*sphi + cphi*spsi*stheta;</div>
<div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;  dR_dPhi(2,1) = cphi*ctheta;</div>
<div class="line"><a name="l00154"></a><span class="lineno">  154</span>&#160; </div>
<div class="line"><a name="l00155"></a><span class="lineno">  155</span>&#160;  dR_dPhi(0,2) = cphi*spsi - cpsi*sphi*stheta;</div>
<div class="line"><a name="l00156"></a><span class="lineno">  156</span>&#160;  dR_dPhi(1,2) = -cphi*cpsi - sphi*spsi*stheta;</div>
<div class="line"><a name="l00157"></a><span class="lineno">  157</span>&#160;  dR_dPhi(2,2) = -ctheta*sphi;</div>
<div class="line"><a name="l00158"></a><span class="lineno">  158</span>&#160; </div>
<div class="line"><a name="l00159"></a><span class="lineno">  159</span>&#160;  dR_dTheta(0,0) = -cpsi*stheta;</div>
<div class="line"><a name="l00160"></a><span class="lineno">  160</span>&#160;  dR_dTheta(1,0) = -spsi*stheta;</div>
<div class="line"><a name="l00161"></a><span class="lineno">  161</span>&#160;  dR_dTheta(2,0) = -ctheta;</div>
<div class="line"><a name="l00162"></a><span class="lineno">  162</span>&#160; </div>
<div class="line"><a name="l00163"></a><span class="lineno">  163</span>&#160;  dR_dTheta(0,1) = cpsi*ctheta*sphi;</div>
<div class="line"><a name="l00164"></a><span class="lineno">  164</span>&#160;  dR_dTheta(1,1) = ctheta*sphi*spsi;</div>
<div class="line"><a name="l00165"></a><span class="lineno">  165</span>&#160;  dR_dTheta(2,1) = -sphi*stheta;</div>
<div class="line"><a name="l00166"></a><span class="lineno">  166</span>&#160; </div>
<div class="line"><a name="l00167"></a><span class="lineno">  167</span>&#160;  dR_dTheta(0,2) = cphi*cpsi*ctheta;</div>
<div class="line"><a name="l00168"></a><span class="lineno">  168</span>&#160;  dR_dTheta(1,2) = cphi*ctheta*spsi;</div>
<div class="line"><a name="l00169"></a><span class="lineno">  169</span>&#160;  dR_dTheta(2,2) = -cphi*stheta;</div>
<div class="line"><a name="l00170"></a><span class="lineno">  170</span>&#160; </div>
<div class="line"><a name="l00171"></a><span class="lineno">  171</span>&#160;  dR_dPsi(0,0) = -ctheta*spsi;</div>
<div class="line"><a name="l00172"></a><span class="lineno">  172</span>&#160;  dR_dPsi(1,0) = cpsi*ctheta;</div>
<div class="line"><a name="l00173"></a><span class="lineno">  173</span>&#160;  dR_dPsi(2,0) = 0.;</div>
<div class="line"><a name="l00174"></a><span class="lineno">  174</span>&#160; </div>
<div class="line"><a name="l00175"></a><span class="lineno">  175</span>&#160;  dR_dPsi(0,1) = -cphi*cpsi - sphi*spsi*stheta;</div>
<div class="line"><a name="l00176"></a><span class="lineno">  176</span>&#160;  dR_dPsi(1,1) = -cphi*spsi + cpsi*sphi*stheta;</div>
<div class="line"><a name="l00177"></a><span class="lineno">  177</span>&#160;  dR_dPsi(2,1) = 0.;</div>
<div class="line"><a name="l00178"></a><span class="lineno">  178</span>&#160; </div>
<div class="line"><a name="l00179"></a><span class="lineno">  179</span>&#160;  dR_dPsi(0,2) = cpsi*sphi - cphi*spsi*stheta;</div>
<div class="line"><a name="l00180"></a><span class="lineno">  180</span>&#160;  dR_dPsi(1,2) = sphi*spsi + cphi*cpsi*stheta;</div>
<div class="line"><a name="l00181"></a><span class="lineno">  181</span>&#160;  dR_dPsi(2,2) = 0.;</div>
<div class="line"><a name="l00182"></a><span class="lineno">  182</span>&#160; </div>
<div class="line"><a name="l00183"></a><span class="lineno">  183</span>&#160;  g[3] = matricesInnerProd(dR_dPhi, R);</div>
<div class="line"><a name="l00184"></a><span class="lineno">  184</span>&#160;  g[4] = matricesInnerProd(dR_dTheta, R);</div>
<div class="line"><a name="l00185"></a><span class="lineno">  185</span>&#160;  g[5] = matricesInnerProd(dR_dPsi, R);</div>
<div class="line"><a name="l00186"></a><span class="lineno">  186</span>&#160;}</div>
<div class="line"><a name="l00187"></a><span class="lineno">  187</span>&#160; </div>
<div class="line"><a name="l00189"></a><span class="lineno">  189</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="classpcl_1_1_generalized_iterative_closest_point.html#aea02526ff54e350a6335d27490d81ca4">  190</a></span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#aea02526ff54e350a6335d27490d81ca4">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::estimateRigidTransformationBFGS</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">PointCloudSource</a> &amp;cloud_src,</div>
<div class="line"><a name="l00191"></a><span class="lineno">  191</span>&#160;                                                                                                  <span class="keyword">const</span> std::vector&lt;int&gt; &amp;indices_src,</div>
<div class="line"><a name="l00192"></a><span class="lineno">  192</span>&#160;                                                                                                  <span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">PointCloudTarget</a> &amp;cloud_tgt,</div>
<div class="line"><a name="l00193"></a><span class="lineno">  193</span>&#160;                                                                                                  <span class="keyword">const</span> std::vector&lt;int&gt; &amp;indices_tgt,</div>
<div class="line"><a name="l00194"></a><span class="lineno">  194</span>&#160;                                                                                                  Eigen::Matrix4f &amp;transformation_matrix)</div>
<div class="line"><a name="l00195"></a><span class="lineno">  195</span>&#160;{</div>
<div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;  <span class="keywordflow">if</span> (indices_src.size () &lt; 4)     <span class="comment">// need at least 4 samples</span></div>
<div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;  {</div>
<div class="line"><a name="l00198"></a><span class="lineno">  198</span>&#160;    PCL_THROW_EXCEPTION (<a class="code" href="classpcl_1_1_not_enough_points_exception.html">NotEnoughPointsException</a>,</div>
<div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;                         <span class="stringliteral">&quot;[pcl::GeneralizedIterativeClosestPoint::estimateRigidTransformationBFGS] Need at least 4 points to estimate a transform! Source and target have &quot;</span> &lt;&lt; indices_src.size () &lt;&lt; <span class="stringliteral">&quot; points!&quot;</span>);</div>
<div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;  }</div>
<div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;  <span class="comment">// Set the initial solution</span></div>
<div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;  Vector6d x = Vector6d::Zero ();</div>
<div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;  x[0] = transformation_matrix (0,3);</div>
<div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;  x[1] = transformation_matrix (1,3);</div>
<div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;  x[2] = transformation_matrix (2,3);</div>
<div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;  x[3] = atan2 (transformation_matrix (2,1), transformation_matrix (2,2));</div>
<div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;  x[4] = asin (-transformation_matrix (2,0));</div>
<div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;  x[5] = atan2 (transformation_matrix (1,0), transformation_matrix (0,0));</div>
<div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160; </div>
<div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;  <span class="comment">// Set temporary pointers</span></div>
<div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;  tmp_src_ = &amp;cloud_src;</div>
<div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;  tmp_tgt_ = &amp;cloud_tgt;</div>
<div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;  tmp_idx_src_ = &amp;indices_src;</div>
<div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;  tmp_idx_tgt_ = &amp;indices_tgt;</div>
<div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160; </div>
<div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;  <span class="comment">// Optimize using forward-difference approximation LM</span></div>
<div class="line"><a name="l00218"></a><span class="lineno">  218</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">double</span> gradient_tol = 1e-2;</div>
<div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;  <a class="code" href="structpcl_1_1_generalized_iterative_closest_point_1_1_optimization_functor_with_indices.html">OptimizationFunctorWithIndices</a> functor(<span class="keyword">this</span>);</div>
<div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;  <a class="code" href="class_b_f_g_s.html">BFGS&lt;OptimizationFunctorWithIndices&gt;</a> bfgs (functor);</div>
<div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;  bfgs.parameters.sigma = 0.01;</div>
<div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;  bfgs.parameters.rho = 0.01;</div>
<div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;  bfgs.parameters.tau1 = 9;</div>
<div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;  bfgs.parameters.tau2 = 0.05;</div>
<div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;  bfgs.parameters.tau3 = 0.5;</div>
<div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;  bfgs.parameters.order = 3;</div>
<div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160; </div>
<div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;  <span class="keywordtype">int</span> inner_iterations_ = 0;</div>
<div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;  <span class="keywordtype">int</span> result = bfgs.minimizeInit (x);</div>
<div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;  result = BFGSSpace::Running;</div>
<div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;  <span class="keywordflow">do</span></div>
<div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;  {</div>
<div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;    inner_iterations_++;</div>
<div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;    result = bfgs.minimizeOneStep (x);</div>
<div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    <span class="keywordflow">if</span>(result)</div>
<div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    {</div>
<div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;    }</div>
<div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;    result = bfgs.testGradient(gradient_tol);</div>
<div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;  } <span class="keywordflow">while</span>(result == BFGSSpace::Running &amp;&amp; inner_iterations_ &lt; max_inner_iterations_);</div>
<div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;  <span class="keywordflow">if</span>(result == BFGSSpace::NoProgress || result == BFGSSpace::Success || inner_iterations_ == max_inner_iterations_)</div>
<div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;  {</div>
<div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;    PCL_DEBUG (<span class="stringliteral">&quot;[pcl::registration::TransformationEstimationBFGS::estimateRigidTransformation]&quot;</span>);</div>
<div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;    PCL_DEBUG (<span class="stringliteral">&quot;BFGS solver finished with exit code %i \n&quot;</span>, result);</div>
<div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;    transformation_matrix.setIdentity();</div>
<div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;    applyState(transformation_matrix, x);</div>
<div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;  }</div>
<div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;  <span class="keywordflow">else</span></div>
<div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;    PCL_THROW_EXCEPTION(<a class="code" href="classpcl_1_1_solver_didnt_converge_exception.html">SolverDidntConvergeException</a>,</div>
<div class="line"><a name="l00250"></a><span class="lineno">  250</span>&#160;                        <span class="stringliteral">&quot;[pcl::&quot;</span> &lt;&lt; getClassName () &lt;&lt; <span class="stringliteral">&quot;::TransformationEstimationBFGS::estimateRigidTransformation] BFGS solver didn&#39;t converge!&quot;</span>);</div>
<div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;}</div>
<div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160; </div>
<div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keyword">inline</span> <span class="keywordtype">double</span></div>
<div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::OptimizationFunctorWithIndices::operator() </a>(<span class="keyword">const</span> Vector6d&amp; x)</div>
<div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;{</div>
<div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;  Eigen::Matrix4f transformation_matrix = gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#af6c01fd53acacf1a488546ad2def4821">base_transformation_</a>;</div>
<div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;  gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a52623ea7fd4588948e7c9f555f25b5c8">applyState</a>(transformation_matrix, x);</div>
<div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;  <span class="keywordtype">double</span> f = 0;</div>
<div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;  <span class="keywordtype">int</span> m = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#aebed534fc98c098ef8b0d0abaef720fd">tmp_idx_src_</a>-&gt;size ());</div>
<div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; m; ++i)</div>
<div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;  {</div>
<div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;    <span class="comment">// The last coordinate, p_src[3] is guaranteed to be set to 1.0 in registration.hpp</span></div>
<div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;    Vector4fMapConst p_src = gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a186170fb2130cdca3e0f5ef8848a78b6">tmp_src_</a>-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[(*gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#aebed534fc98c098ef8b0d0abaef720fd">tmp_idx_src_</a>)[i]].getVector4fMap ();</div>
<div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;    <span class="comment">// The last coordinate, p_tgt[3] is guaranteed to be set to 1.0 in registration.hpp</span></div>
<div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;    Vector4fMapConst p_tgt = gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a7c1850fa0ac8df790aa9791a8d0f4343">tmp_tgt_</a>-&gt;<a class="code" href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">points</a>[(*gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#acd1d3d3abcca095774c1d2a7d1a24941">tmp_idx_tgt_</a>)[i]].getVector4fMap ();</div>
<div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;    Eigen::Vector4f pp (transformation_matrix * p_src);</div>
<div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;    <span class="comment">// Estimate the distance (cost function)</span></div>
<div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;    <span class="comment">// The last coordiante is still guaranteed to be set to 1.0</span></div>
<div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;    Eigen::Vector3d res(pp[0] - p_tgt[0], pp[1] - p_tgt[1], pp[2] - p_tgt[2]);</div>
<div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;    Eigen::Vector3d temp (gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#ad095300e41f27b087fbace58aa2500fa">mahalanobis</a>((*gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#aebed534fc98c098ef8b0d0abaef720fd">tmp_idx_src_</a>)[i]) * res);</div>
<div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;    <span class="comment">//increment= res&#39;*temp/num_matches = temp&#39;*M*temp/num_matches (we postpone 1/num_matches after the loop closes)</span></div>
<div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;    f+= double(res.transpose() * temp);</div>
<div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;  }</div>
<div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;  <span class="keywordflow">return</span> f/m;</div>
<div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;}</div>
<div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160; </div>
<div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::OptimizationFunctorWithIndices::df</a> (<span class="keyword">const</span> Vector6d&amp; x, Vector6d&amp; g)</div>
<div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;{</div>
<div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;  Eigen::Matrix4f transformation_matrix = gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#af6c01fd53acacf1a488546ad2def4821">base_transformation_</a>;</div>
<div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;  gicp_-&gt;applyState(transformation_matrix, x);</div>
<div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;  <span class="comment">//Zero out g</span></div>
<div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;  g.setZero ();</div>
<div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;  <span class="comment">//Eigen::Vector3d g_t = g.head&lt;3&gt; ();</span></div>
<div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;  Eigen::Matrix3d R = Eigen::Matrix3d::Zero ();</div>
<div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;  <span class="keywordtype">int</span> m = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (gicp_-&gt;tmp_idx_src_-&gt;size ());</div>
<div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; m; ++i)</div>
<div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;  {</div>
<div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;    <span class="comment">// The last coordinate, p_src[3] is guaranteed to be set to 1.0 in registration.hpp</span></div>
<div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;    Vector4fMapConst p_src = gicp_-&gt;tmp_src_-&gt;points[(*gicp_-&gt;tmp_idx_src_)[i]].getVector4fMap ();</div>
<div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;    <span class="comment">// The last coordinate, p_tgt[3] is guaranteed to be set to 1.0 in registration.hpp</span></div>
<div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;    Vector4fMapConst p_tgt = gicp_-&gt;tmp_tgt_-&gt;points[(*gicp_-&gt;tmp_idx_tgt_)[i]].getVector4fMap ();</div>
<div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160; </div>
<div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;    Eigen::Vector4f pp (transformation_matrix * p_src);</div>
<div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;    <span class="comment">// The last coordiante is still guaranteed to be set to 1.0</span></div>
<div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;    Eigen::Vector3d res (pp[0] - p_tgt[0], pp[1] - p_tgt[1], pp[2] - p_tgt[2]);</div>
<div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;    <span class="comment">// temp = M*res</span></div>
<div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;    Eigen::Vector3d temp (gicp_-&gt;mahalanobis ((*gicp_-&gt;tmp_idx_src_)[i]) * res);</div>
<div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;    <span class="comment">// Increment translation gradient</span></div>
<div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;    <span class="comment">// g.head&lt;3&gt; ()+= 2*M*res/num_matches (we postpone 2/num_matches after the loop closes)</span></div>
<div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;    g.head&lt;3&gt; ()+= temp;</div>
<div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;    <span class="comment">// Increment rotation gradient</span></div>
<div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;    pp = gicp_-&gt;base_transformation_ * p_src;</div>
<div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;    Eigen::Vector3d p_src3 (pp[0], pp[1], pp[2]);</div>
<div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;    R+= p_src3 * temp.transpose();</div>
<div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;  }</div>
<div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;  g.head&lt;3&gt; ()*= 2.0/m;</div>
<div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;  R*= 2.0/m;</div>
<div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;  gicp_-&gt;computeRDerivative(x, R, g);</div>
<div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;}</div>
<div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160; </div>
<div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::OptimizationFunctorWithIndices::fdf</a> (<span class="keyword">const</span> Vector6d&amp; x, <span class="keywordtype">double</span>&amp; f, Vector6d&amp; g)</div>
<div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;{</div>
<div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;  Eigen::Matrix4f transformation_matrix = gicp_-&gt;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#af6c01fd53acacf1a488546ad2def4821">base_transformation_</a>;</div>
<div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;  gicp_-&gt;applyState(transformation_matrix, x);</div>
<div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;  f = 0;</div>
<div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;  g.setZero ();</div>
<div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;  Eigen::Matrix3d R = Eigen::Matrix3d::Zero ();</div>
<div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">int</span> m = <span class="keyword">static_cast&lt;</span><span class="keyword">const </span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (gicp_-&gt;tmp_idx_src_-&gt;size ());</div>
<div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; m; ++i)</div>
<div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;  {</div>
<div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;    <span class="comment">// The last coordinate, p_src[3] is guaranteed to be set to 1.0 in registration.hpp</span></div>
<div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;    Vector4fMapConst p_src = gicp_-&gt;tmp_src_-&gt;points[(*gicp_-&gt;tmp_idx_src_)[i]].getVector4fMap ();</div>
<div class="line"><a name="l00328"></a><span class="lineno">  328</span>&#160;    <span class="comment">// The last coordinate, p_tgt[3] is guaranteed to be set to 1.0 in registration.hpp</span></div>
<div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    Vector4fMapConst p_tgt = gicp_-&gt;tmp_tgt_-&gt;points[(*gicp_-&gt;tmp_idx_tgt_)[i]].getVector4fMap ();</div>
<div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;    Eigen::Vector4f pp (transformation_matrix * p_src);</div>
<div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;    <span class="comment">// The last coordiante is still guaranteed to be set to 1.0</span></div>
<div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;    Eigen::Vector3d res (pp[0] - p_tgt[0], pp[1] - p_tgt[1], pp[2] - p_tgt[2]);</div>
<div class="line"><a name="l00333"></a><span class="lineno">  333</span>&#160;    <span class="comment">// temp = M*res</span></div>
<div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;    Eigen::Vector3d temp (gicp_-&gt;mahalanobis((*gicp_-&gt;tmp_idx_src_)[i]) * res);</div>
<div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    <span class="comment">// Increment total error</span></div>
<div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;    f+= double(res.transpose() * temp);</div>
<div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;    <span class="comment">// Increment translation gradient</span></div>
<div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;    <span class="comment">// g.head&lt;3&gt; ()+= 2*M*res/num_matches (we postpone 2/num_matches after the loop closes)</span></div>
<div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;    g.head&lt;3&gt; ()+= temp;</div>
<div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    pp = gicp_-&gt;base_transformation_ * p_src;</div>
<div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;    Eigen::Vector3d p_src3 (pp[0], pp[1], pp[2]);</div>
<div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;    <span class="comment">// Increment rotation gradient</span></div>
<div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    R+= p_src3 * temp.transpose();</div>
<div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;  }</div>
<div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;  f/= double(m);</div>
<div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;  g.head&lt;3&gt; ()*= <span class="keywordtype">double</span>(2.0/m);</div>
<div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;  R*= 2.0/m;</div>
<div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;  gicp_-&gt;computeRDerivative(x, R, g);</div>
<div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;}</div>
<div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160; </div>
<div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keyword">inline</span> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00353"></a><span class="lineno"><a class="line" href="classpcl_1_1_generalized_iterative_closest_point.html#a21e902199045b4835c78bed15a3b7367">  353</a></span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a21e902199045b4835c78bed15a3b7367">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::computeTransformation</a> (<a class="code" href="classpcl_1_1_point_cloud.html">PointCloudSource</a> &amp;output, <span class="keyword">const</span> Eigen::Matrix4f&amp; guess)</div>
<div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;{</div>
<div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;  <a class="code" href="classpcl_1_1_registration.html#ae210269f0404556b8dd7f4306084a91d">pcl::IterativeClosestPoint&lt;PointSource, PointTarget&gt;::initComputeReciprocal</a> ();</div>
<div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;  <span class="keyword">using namespace </span>std;</div>
<div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;  <span class="comment">// Difference between consecutive transforms</span></div>
<div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;  <span class="keywordtype">double</span> delta = 0;</div>
<div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;  <span class="comment">// Get the size of the target</span></div>
<div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;  <span class="keyword">const</span> <span class="keywordtype">size_t</span> N = <a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;size ();</div>
<div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;  <span class="comment">// Set the mahalanobis matrices to identity</span></div>
<div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;  <a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a42077263d639013b40d73f672a104b09">mahalanobis_</a>.resize (N, Eigen::Matrix3d::Identity ());</div>
<div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;  <span class="comment">// Compute target cloud covariance matrices</span></div>
<div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;  <span class="keywordflow">if</span> ((!<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a81ed891465b173c8ee3e22cea593de3c">target_covariances_</a>) || (<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a81ed891465b173c8ee3e22cea593de3c">target_covariances_</a>-&gt;empty ()))</div>
<div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;  {</div>
<div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;    <a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a81ed891465b173c8ee3e22cea593de3c">target_covariances_</a>.reset (<span class="keyword">new</span> MatricesVector);  </div>
<div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;    computeCovariances&lt;PointTarget&gt; (<a class="code" href="classpcl_1_1_registration.html#af9ac08a379a3b5db44c5c502cf6a882e">target_</a>, <a class="code" href="classpcl_1_1_registration.html#a79b6170328705f29854aba00c4feb66d">tree_</a>, *<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a81ed891465b173c8ee3e22cea593de3c">target_covariances_</a>);</div>
<div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;  }</div>
<div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;  <span class="comment">// Compute input cloud covariance matrices</span></div>
<div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;  <span class="keywordflow">if</span> ((!<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#ac86cb83cfcca7d2a5664369dbc0f210c">input_covariances_</a>) || (<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#ac86cb83cfcca7d2a5664369dbc0f210c">input_covariances_</a>-&gt;empty ()))</div>
<div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;  {</div>
<div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;    <a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#ac86cb83cfcca7d2a5664369dbc0f210c">input_covariances_</a>.reset (<span class="keyword">new</span> MatricesVector);</div>
<div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;    computeCovariances&lt;PointSource&gt; (<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>, <a class="code" href="classpcl_1_1_registration.html#a3362d946f4b60e2628dc02e2af1f24fd">tree_reciprocal_</a>, *<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#ac86cb83cfcca7d2a5664369dbc0f210c">input_covariances_</a>);</div>
<div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160;  }</div>
<div class="line"><a name="l00375"></a><span class="lineno">  375</span>&#160; </div>
<div class="line"><a name="l00376"></a><span class="lineno">  376</span>&#160;  <a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#af6c01fd53acacf1a488546ad2def4821">base_transformation_</a> = Eigen::Matrix4f::Identity();</div>
<div class="line"><a name="l00377"></a><span class="lineno">  377</span>&#160;  <a class="code" href="classpcl_1_1_registration.html#a6957c3193d73098cb0535d6625d591d4">nr_iterations_</a> = 0;</div>
<div class="line"><a name="l00378"></a><span class="lineno">  378</span>&#160;  <a class="code" href="classpcl_1_1_registration.html#a8e94793b677e107410ebb29ea2f931e9">converged_</a> = <span class="keyword">false</span>;</div>
<div class="line"><a name="l00379"></a><span class="lineno">  379</span>&#160;  <span class="keywordtype">double</span> dist_threshold = <a class="code" href="classpcl_1_1_registration.html#a15aa975f33a8f22573bad118ddda10dd">corr_dist_threshold_</a> * <a class="code" href="classpcl_1_1_registration.html#a15aa975f33a8f22573bad118ddda10dd">corr_dist_threshold_</a>;</div>
<div class="line"><a name="l00380"></a><span class="lineno">  380</span>&#160;  std::vector&lt;int&gt; nn_indices (1);</div>
<div class="line"><a name="l00381"></a><span class="lineno">  381</span>&#160;  std::vector&lt;float&gt; nn_dists (1);</div>
<div class="line"><a name="l00382"></a><span class="lineno">  382</span>&#160; </div>
<div class="line"><a name="l00383"></a><span class="lineno">  383</span>&#160;  <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a>(output, output, guess);</div>
<div class="line"><a name="l00384"></a><span class="lineno">  384</span>&#160; </div>
<div class="line"><a name="l00385"></a><span class="lineno">  385</span>&#160;  <span class="keywordflow">while</span>(!<a class="code" href="classpcl_1_1_registration.html#a8e94793b677e107410ebb29ea2f931e9">converged_</a>)</div>
<div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;  {</div>
<div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;    <span class="keywordtype">size_t</span> cnt = 0;</div>
<div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;    std::vector&lt;int&gt; source_indices (<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;size ());</div>
<div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;    std::vector&lt;int&gt; target_indices (<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>-&gt;size ());</div>
<div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160; </div>
<div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;    <span class="comment">// guess corresponds to base_t and transformation_ to t</span></div>
<div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;    Eigen::Matrix4d transform_R = Eigen::Matrix4d::Zero ();</div>
<div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;    <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> i = 0; i &lt; 4; i++)</div>
<div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;      <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> j = 0; j &lt; 4; j++)</div>
<div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> k = 0; k &lt; 4; k++)</div>
<div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;          transform_R(i,j)+= double(<a class="code" href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">transformation_</a>(i,k)) * double(guess(k,j));</div>
<div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160; </div>
<div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;    Eigen::Matrix3d R = transform_R.topLeftCorner&lt;3,3&gt; ();</div>
<div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160; </div>
<div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;    <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i &lt; N; i++)</div>
<div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;    {</div>
<div class="line"><a name="l00402"></a><span class="lineno">  402</span>&#160;      PointSource query = output[i];</div>
<div class="line"><a name="l00403"></a><span class="lineno">  403</span>&#160;      query.getVector4fMap () = <a class="code" href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">transformation_</a> * query.getVector4fMap ();</div>
<div class="line"><a name="l00404"></a><span class="lineno">  404</span>&#160; </div>
<div class="line"><a name="l00405"></a><span class="lineno">  405</span>&#160;      <span class="keywordflow">if</span> (!<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#ae379911827eaacf4ce6d1c6f1dcdb0b6">searchForNeighbors</a> (query, nn_indices, nn_dists))</div>
<div class="line"><a name="l00406"></a><span class="lineno">  406</span>&#160;      {</div>
<div class="line"><a name="l00407"></a><span class="lineno">  407</span>&#160;        PCL_ERROR (<span class="stringliteral">&quot;[pcl::%s::computeTransformation] Unable to find a nearest neighbor in the target dataset for point %d in the source!\n&quot;</span>, <a class="code" href="classpcl_1_1_registration.html#a26eae6a42450893ca1c2ed81560159f2">getClassName</a> ().c_str (), (*<a class="code" href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">indices_</a>)[i]);</div>
<div class="line"><a name="l00408"></a><span class="lineno">  408</span>&#160;        <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00409"></a><span class="lineno">  409</span>&#160;      }</div>
<div class="line"><a name="l00410"></a><span class="lineno">  410</span>&#160; </div>
<div class="line"><a name="l00411"></a><span class="lineno">  411</span>&#160;      <span class="comment">// Check if the distance to the nearest neighbor is smaller than the user imposed threshold</span></div>
<div class="line"><a name="l00412"></a><span class="lineno">  412</span>&#160;      <span class="keywordflow">if</span> (nn_dists[0] &lt; dist_threshold)</div>
<div class="line"><a name="l00413"></a><span class="lineno">  413</span>&#160;      {</div>
<div class="line"><a name="l00414"></a><span class="lineno">  414</span>&#160;        Eigen::Matrix3d &amp;C1 = (*input_covariances_)[i];</div>
<div class="line"><a name="l00415"></a><span class="lineno">  415</span>&#160;        Eigen::Matrix3d &amp;C2 = (*target_covariances_)[nn_indices[0]];</div>
<div class="line"><a name="l00416"></a><span class="lineno">  416</span>&#160;        Eigen::Matrix3d &amp;M = <a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a42077263d639013b40d73f672a104b09">mahalanobis_</a>[i];</div>
<div class="line"><a name="l00417"></a><span class="lineno">  417</span>&#160;        <span class="comment">// M = R*C1</span></div>
<div class="line"><a name="l00418"></a><span class="lineno">  418</span>&#160;        M = R * C1;</div>
<div class="line"><a name="l00419"></a><span class="lineno">  419</span>&#160;        <span class="comment">// temp = M*R&#39; + C2 = R*C1*R&#39; + C2</span></div>
<div class="line"><a name="l00420"></a><span class="lineno">  420</span>&#160;        Eigen::Matrix3d temp = M * R.transpose();</div>
<div class="line"><a name="l00421"></a><span class="lineno">  421</span>&#160;        temp+= C2;</div>
<div class="line"><a name="l00422"></a><span class="lineno">  422</span>&#160;        <span class="comment">// M = temp^-1</span></div>
<div class="line"><a name="l00423"></a><span class="lineno">  423</span>&#160;        M = temp.inverse ();</div>
<div class="line"><a name="l00424"></a><span class="lineno">  424</span>&#160;        source_indices[cnt] = <span class="keyword">static_cast&lt;</span><span class="keywordtype">int</span><span class="keyword">&gt;</span> (i);</div>
<div class="line"><a name="l00425"></a><span class="lineno">  425</span>&#160;        target_indices[cnt] = nn_indices[0];</div>
<div class="line"><a name="l00426"></a><span class="lineno">  426</span>&#160;        cnt++;</div>
<div class="line"><a name="l00427"></a><span class="lineno">  427</span>&#160;      }</div>
<div class="line"><a name="l00428"></a><span class="lineno">  428</span>&#160;    }</div>
<div class="line"><a name="l00429"></a><span class="lineno">  429</span>&#160;    <span class="comment">// Resize to the actual number of valid correspondences</span></div>
<div class="line"><a name="l00430"></a><span class="lineno">  430</span>&#160;    source_indices.resize(cnt); target_indices.resize(cnt);</div>
<div class="line"><a name="l00431"></a><span class="lineno">  431</span>&#160;    <span class="comment">/* optimize transformation using the current assignment and Mahalanobis metrics*/</span></div>
<div class="line"><a name="l00432"></a><span class="lineno">  432</span>&#160;    <a class="code" href="classpcl_1_1_registration.html#a8d0064ba2f733ef07476f42de09a656f">previous_transformation_</a> = <a class="code" href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">transformation_</a>;</div>
<div class="line"><a name="l00433"></a><span class="lineno">  433</span>&#160;    <span class="comment">//optimization right here</span></div>
<div class="line"><a name="l00434"></a><span class="lineno">  434</span>&#160;    <span class="keywordflow">try</span></div>
<div class="line"><a name="l00435"></a><span class="lineno">  435</span>&#160;    {</div>
<div class="line"><a name="l00436"></a><span class="lineno">  436</span>&#160;      rigid_transformation_estimation_(output, source_indices, *<a class="code" href="classpcl_1_1_registration.html#af9ac08a379a3b5db44c5c502cf6a882e">target_</a>, target_indices, <a class="code" href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">transformation_</a>);</div>
<div class="line"><a name="l00437"></a><span class="lineno">  437</span>&#160;      <span class="comment">/* compute the delta from this iteration */</span></div>
<div class="line"><a name="l00438"></a><span class="lineno">  438</span>&#160;      delta = 0.;</div>
<div class="line"><a name="l00439"></a><span class="lineno">  439</span>&#160;      <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k &lt; 4; k++) {</div>
<div class="line"><a name="l00440"></a><span class="lineno">  440</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> l = 0; l &lt; 4; l++) {</div>
<div class="line"><a name="l00441"></a><span class="lineno">  441</span>&#160;          <span class="keywordtype">double</span> ratio = 1;</div>
<div class="line"><a name="l00442"></a><span class="lineno">  442</span>&#160;          <span class="keywordflow">if</span>(k &lt; 3 &amp;&amp; l &lt; 3) <span class="comment">// rotation part of the transform</span></div>
<div class="line"><a name="l00443"></a><span class="lineno">  443</span>&#160;            ratio = 1./<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a6b3c435a32ae28d6c4bee571d4c675f3">rotation_epsilon_</a>;</div>
<div class="line"><a name="l00444"></a><span class="lineno">  444</span>&#160;          <span class="keywordflow">else</span></div>
<div class="line"><a name="l00445"></a><span class="lineno">  445</span>&#160;            ratio = 1./<a class="code" href="classpcl_1_1_registration.html#adbd6519634f433c0be2fd640c0c75108">transformation_epsilon_</a>;</div>
<div class="line"><a name="l00446"></a><span class="lineno">  446</span>&#160;          <span class="keywordtype">double</span> c_delta = ratio*fabs(<a class="code" href="classpcl_1_1_registration.html#a8d0064ba2f733ef07476f42de09a656f">previous_transformation_</a>(k,l) - <a class="code" href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">transformation_</a>(k,l));</div>
<div class="line"><a name="l00447"></a><span class="lineno">  447</span>&#160;          <span class="keywordflow">if</span>(c_delta &gt; delta)</div>
<div class="line"><a name="l00448"></a><span class="lineno">  448</span>&#160;            delta = c_delta;</div>
<div class="line"><a name="l00449"></a><span class="lineno">  449</span>&#160;        }</div>
<div class="line"><a name="l00450"></a><span class="lineno">  450</span>&#160;      }</div>
<div class="line"><a name="l00451"></a><span class="lineno">  451</span>&#160;    }</div>
<div class="line"><a name="l00452"></a><span class="lineno">  452</span>&#160;    <span class="keywordflow">catch</span> (<a class="code" href="classpcl_1_1_p_c_l_exception.html">PCLException</a> &amp;e)</div>
<div class="line"><a name="l00453"></a><span class="lineno">  453</span>&#160;    {</div>
<div class="line"><a name="l00454"></a><span class="lineno">  454</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::computeTransformation] Optimization issue %s\n&quot;</span>, <a class="code" href="classpcl_1_1_registration.html#a26eae6a42450893ca1c2ed81560159f2">getClassName</a> ().c_str (), e.what ());</div>
<div class="line"><a name="l00455"></a><span class="lineno">  455</span>&#160;      <span class="keywordflow">break</span>;</div>
<div class="line"><a name="l00456"></a><span class="lineno">  456</span>&#160;    }</div>
<div class="line"><a name="l00457"></a><span class="lineno">  457</span>&#160;    <a class="code" href="classpcl_1_1_registration.html#a6957c3193d73098cb0535d6625d591d4">nr_iterations_</a>++;</div>
<div class="line"><a name="l00458"></a><span class="lineno">  458</span>&#160;    <span class="comment">// Check for convergence</span></div>
<div class="line"><a name="l00459"></a><span class="lineno">  459</span>&#160;    <span class="keywordflow">if</span> (<a class="code" href="classpcl_1_1_registration.html#a6957c3193d73098cb0535d6625d591d4">nr_iterations_</a> &gt;= <a class="code" href="classpcl_1_1_registration.html#aa776d097d20137f2702a275d931989d2">max_iterations_</a> || delta &lt; 1)</div>
<div class="line"><a name="l00460"></a><span class="lineno">  460</span>&#160;    {</div>
<div class="line"><a name="l00461"></a><span class="lineno">  461</span>&#160;      <a class="code" href="classpcl_1_1_registration.html#a8e94793b677e107410ebb29ea2f931e9">converged_</a> = <span class="keyword">true</span>;</div>
<div class="line"><a name="l00462"></a><span class="lineno">  462</span>&#160;      <a class="code" href="classpcl_1_1_registration.html#a8d0064ba2f733ef07476f42de09a656f">previous_transformation_</a> = <a class="code" href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">transformation_</a>;</div>
<div class="line"><a name="l00463"></a><span class="lineno">  463</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::computeTransformation] Convergence reached. Number of iterations: %d out of %d. Transformation difference: %f\n&quot;</span>,</div>
<div class="line"><a name="l00464"></a><span class="lineno">  464</span>&#160;                 <a class="code" href="classpcl_1_1_registration.html#a26eae6a42450893ca1c2ed81560159f2">getClassName</a> ().c_str (), <a class="code" href="classpcl_1_1_registration.html#a6957c3193d73098cb0535d6625d591d4">nr_iterations_</a>, <a class="code" href="classpcl_1_1_registration.html#aa776d097d20137f2702a275d931989d2">max_iterations_</a>, (<a class="code" href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">transformation_</a> - <a class="code" href="classpcl_1_1_registration.html#a8d0064ba2f733ef07476f42de09a656f">previous_transformation_</a>).array ().abs ().sum ());</div>
<div class="line"><a name="l00465"></a><span class="lineno">  465</span>&#160;    }</div>
<div class="line"><a name="l00466"></a><span class="lineno">  466</span>&#160;    <span class="keywordflow">else</span></div>
<div class="line"><a name="l00467"></a><span class="lineno">  467</span>&#160;      PCL_DEBUG (<span class="stringliteral">&quot;[pcl::%s::computeTransformation] Convergence failed\n&quot;</span>, <a class="code" href="classpcl_1_1_registration.html#a26eae6a42450893ca1c2ed81560159f2">getClassName</a> ().c_str ());</div>
<div class="line"><a name="l00468"></a><span class="lineno">  468</span>&#160;  }</div>
<div class="line"><a name="l00469"></a><span class="lineno">  469</span>&#160;  <a class="code" href="classpcl_1_1_registration.html#a023e79a041ee70e8383654432cf5a71e">final_transformation_</a> = <a class="code" href="classpcl_1_1_registration.html#a8d0064ba2f733ef07476f42de09a656f">previous_transformation_</a> * guess;</div>
<div class="line"><a name="l00470"></a><span class="lineno">  470</span>&#160; </div>
<div class="line"><a name="l00471"></a><span class="lineno">  471</span>&#160;  <span class="comment">// Transform the point cloud</span></div>
<div class="line"><a name="l00472"></a><span class="lineno">  472</span>&#160;  <a class="code" href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a> (*<a class="code" href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">input_</a>, output, <a class="code" href="classpcl_1_1_registration.html#a023e79a041ee70e8383654432cf5a71e">final_transformation_</a>);</div>
<div class="line"><a name="l00473"></a><span class="lineno">  473</span>&#160;}</div>
<div class="line"><a name="l00474"></a><span class="lineno">  474</span>&#160; </div>
<div class="line"><a name="l00475"></a><span class="lineno">  475</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> Po<span class="keywordtype">int</span>Source, <span class="keyword">typename</span> Po<span class="keywordtype">int</span>Target&gt; <span class="keywordtype">void</span></div>
<div class="line"><a name="l00476"></a><span class="lineno"><a class="line" href="classpcl_1_1_generalized_iterative_closest_point.html#a52623ea7fd4588948e7c9f555f25b5c8">  476</a></span>&#160;<a class="code" href="classpcl_1_1_generalized_iterative_closest_point.html#a52623ea7fd4588948e7c9f555f25b5c8">pcl::GeneralizedIterativeClosestPoint&lt;PointSource, PointTarget&gt;::applyState</a>(Eigen::Matrix4f &amp;t, <span class="keyword">const</span> Vector6d&amp; x)<span class="keyword"> const</span></div>
<div class="line"><a name="l00477"></a><span class="lineno">  477</span>&#160;<span class="keyword"></span>{</div>
<div class="line"><a name="l00478"></a><span class="lineno">  478</span>&#160;  <span class="comment">// !!! CAUTION Stanford GICP uses the Z Y X euler angles convention</span></div>
<div class="line"><a name="l00479"></a><span class="lineno">  479</span>&#160;  Eigen::Matrix3f R;</div>
<div class="line"><a name="l00480"></a><span class="lineno">  480</span>&#160;  R = Eigen::AngleAxisf (<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (x[5]), Eigen::Vector3f::UnitZ ())</div>
<div class="line"><a name="l00481"></a><span class="lineno">  481</span>&#160;    * Eigen::AngleAxisf (<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (x[4]), Eigen::Vector3f::UnitY ())</div>
<div class="line"><a name="l00482"></a><span class="lineno">  482</span>&#160;    * Eigen::AngleAxisf (<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (x[3]), Eigen::Vector3f::UnitX ());</div>
<div class="line"><a name="l00483"></a><span class="lineno">  483</span>&#160;  t.topLeftCorner&lt;3,3&gt; ().matrix () = R * t.topLeftCorner&lt;3,3&gt; ().matrix ();</div>
<div class="line"><a name="l00484"></a><span class="lineno">  484</span>&#160;  Eigen::Vector4f T (<span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (x[0]), <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (x[1]), <span class="keyword">static_cast&lt;</span><span class="keywordtype">float</span><span class="keyword">&gt;</span> (x[2]), 0.0f);</div>
<div class="line"><a name="l00485"></a><span class="lineno">  485</span>&#160;  t.col (3) += T;</div>
<div class="line"><a name="l00486"></a><span class="lineno">  486</span>&#160;}</div>
<div class="line"><a name="l00487"></a><span class="lineno">  487</span>&#160; </div>
<div class="line"><a name="l00488"></a><span class="lineno">  488</span>&#160;<span class="preprocessor">#endif </span><span class="comment">//PCL_REGISTRATION_IMPL_GICP_HPP_</span></div>
<div class="ttc" id="aclass_b_f_g_s_html"><div class="ttname"><a href="class_b_f_g_s.html">BFGS</a></div><div class="ttdef"><b>Definition:</b> bfgs.h:115</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html">pcl::GeneralizedIterativeClosestPoint</a></div><div class="ttdoc">GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest ...</div><div class="ttdef"><b>Definition:</b> gicp.h:61</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a186170fb2130cdca3e0f5ef8848a78b6"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a186170fb2130cdca3e0f5ef8848a78b6">pcl::GeneralizedIterativeClosestPoint::tmp_src_</a></div><div class="ttdeci">const PointCloudSource * tmp_src_</div><div class="ttdoc">Temporary pointer to the source dataset.</div><div class="ttdef"><b>Definition:</b> gicp.h:278</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a21e902199045b4835c78bed15a3b7367"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a21e902199045b4835c78bed15a3b7367">pcl::GeneralizedIterativeClosestPoint::computeTransformation</a></div><div class="ttdeci">void computeTransformation(PointCloudSource &amp;output, const Eigen::Matrix4f &amp;guess)</div><div class="ttdoc">Rigid transformation computation method with initial guess.</div><div class="ttdef"><b>Definition:</b> gicp.hpp:353</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a42077263d639013b40d73f672a104b09"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a42077263d639013b40d73f672a104b09">pcl::GeneralizedIterativeClosestPoint::mahalanobis_</a></div><div class="ttdeci">std::vector&lt; Eigen::Matrix3d &gt; mahalanobis_</div><div class="ttdoc">Mahalanobis matrices holder.</div><div class="ttdef"><b>Definition:</b> gicp.h:297</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a4307aa8507e98a86183d3ba4cb5400d0"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a4307aa8507e98a86183d3ba4cb5400d0">pcl::GeneralizedIterativeClosestPoint::computeCovariances</a></div><div class="ttdeci">void computeCovariances(typename pcl::PointCloud&lt; PointT &gt;::ConstPtr cloud, const typename pcl::search::KdTree&lt; PointT &gt;::Ptr tree, MatricesVector &amp;cloud_covariances)</div><div class="ttdoc">compute points covariances matrices according to the K nearest neighbors. K is set via setCorresponde...</div><div class="ttdef"><b>Definition:</b> gicp.hpp:57</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a52623ea7fd4588948e7c9f555f25b5c8"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a52623ea7fd4588948e7c9f555f25b5c8">pcl::GeneralizedIterativeClosestPoint::applyState</a></div><div class="ttdeci">void applyState(Eigen::Matrix4f &amp;t, const Vector6d &amp;x) const</div><div class="ttdoc">compute transformation matrix from transformation matrix</div><div class="ttdef"><b>Definition:</b> gicp.hpp:476</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a6b3c435a32ae28d6c4bee571d4c675f3"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a6b3c435a32ae28d6c4bee571d4c675f3">pcl::GeneralizedIterativeClosestPoint::rotation_epsilon_</a></div><div class="ttdeci">double rotation_epsilon_</div><div class="ttdef"><b>Definition:</b> gicp.h:272</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a796c0d782df55e6b35f726a5f6b34097"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a796c0d782df55e6b35f726a5f6b34097">pcl::GeneralizedIterativeClosestPoint::setInputCloud</a></div><div class="ttdeci">void setInputCloud(const PointCloudSourceConstPtr &amp;cloud)</div><div class="ttdoc">Provide a pointer to the input dataset</div><div class="ttdef"><b>Definition:</b> gicp.hpp:48</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a7c1850fa0ac8df790aa9791a8d0f4343"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a7c1850fa0ac8df790aa9791a8d0f4343">pcl::GeneralizedIterativeClosestPoint::tmp_tgt_</a></div><div class="ttdeci">const PointCloudTarget * tmp_tgt_</div><div class="ttdoc">Temporary pointer to the target dataset.</div><div class="ttdef"><b>Definition:</b> gicp.h:281</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_a81ed891465b173c8ee3e22cea593de3c"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#a81ed891465b173c8ee3e22cea593de3c">pcl::GeneralizedIterativeClosestPoint::target_covariances_</a></div><div class="ttdeci">MatricesVectorPtr target_covariances_</div><div class="ttdoc">Target cloud points covariances.</div><div class="ttdef"><b>Definition:</b> gicp.h:294</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_ac86cb83cfcca7d2a5664369dbc0f210c"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#ac86cb83cfcca7d2a5664369dbc0f210c">pcl::GeneralizedIterativeClosestPoint::input_covariances_</a></div><div class="ttdeci">MatricesVectorPtr input_covariances_</div><div class="ttdoc">Input cloud points covariances.</div><div class="ttdef"><b>Definition:</b> gicp.h:291</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_acce93f0ea69ea9d9798529cc6e1083e0"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#acce93f0ea69ea9d9798529cc6e1083e0">pcl::GeneralizedIterativeClosestPoint::computeRDerivative</a></div><div class="ttdeci">void computeRDerivative(const Vector6d &amp;x, const Eigen::Matrix3d &amp;R, Vector6d &amp;g) const</div><div class="ttdoc">Computes rotation matrix derivative. rotation matrix is obtainded from rotation angles x[3],...</div><div class="ttdef"><b>Definition:</b> gicp.hpp:135</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_acd1d3d3abcca095774c1d2a7d1a24941"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#acd1d3d3abcca095774c1d2a7d1a24941">pcl::GeneralizedIterativeClosestPoint::tmp_idx_tgt_</a></div><div class="ttdeci">const std::vector&lt; int &gt; * tmp_idx_tgt_</div><div class="ttdoc">Temporary pointer to the target dataset indices.</div><div class="ttdef"><b>Definition:</b> gicp.h:287</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_ad095300e41f27b087fbace58aa2500fa"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#ad095300e41f27b087fbace58aa2500fa">pcl::GeneralizedIterativeClosestPoint::mahalanobis</a></div><div class="ttdeci">const Eigen::Matrix3d &amp; mahalanobis(size_t index) const</div><div class="ttdef"><b>Definition:</b> gicp.h:200</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_ae379911827eaacf4ce6d1c6f1dcdb0b6"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#ae379911827eaacf4ce6d1c6f1dcdb0b6">pcl::GeneralizedIterativeClosestPoint::searchForNeighbors</a></div><div class="ttdeci">bool searchForNeighbors(const PointSource &amp;query, std::vector&lt; int &gt; &amp;index, std::vector&lt; float &gt; &amp;distance)</div><div class="ttdoc">Search for the closest nearest neighbor of a given point.</div><div class="ttdef"><b>Definition:</b> gicp.h:342</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_aea02526ff54e350a6335d27490d81ca4"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#aea02526ff54e350a6335d27490d81ca4">pcl::GeneralizedIterativeClosestPoint::estimateRigidTransformationBFGS</a></div><div class="ttdeci">void estimateRigidTransformationBFGS(const PointCloudSource &amp;cloud_src, const std::vector&lt; int &gt; &amp;indices_src, const PointCloudTarget &amp;cloud_tgt, const std::vector&lt; int &gt; &amp;indices_tgt, Eigen::Matrix4f &amp;transformation_matrix)</div><div class="ttdoc">Estimate a rigid rotation transformation between a source and a target point cloud using an iterative...</div><div class="ttdef"><b>Definition:</b> gicp.hpp:190</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_aebed534fc98c098ef8b0d0abaef720fd"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#aebed534fc98c098ef8b0d0abaef720fd">pcl::GeneralizedIterativeClosestPoint::tmp_idx_src_</a></div><div class="ttdeci">const std::vector&lt; int &gt; * tmp_idx_src_</div><div class="ttdoc">Temporary pointer to the source dataset indices.</div><div class="ttdef"><b>Definition:</b> gicp.h:284</div></div>
<div class="ttc" id="aclasspcl_1_1_generalized_iterative_closest_point_html_af6c01fd53acacf1a488546ad2def4821"><div class="ttname"><a href="classpcl_1_1_generalized_iterative_closest_point.html#af6c01fd53acacf1a488546ad2def4821">pcl::GeneralizedIterativeClosestPoint::base_transformation_</a></div><div class="ttdeci">Eigen::Matrix4f base_transformation_</div><div class="ttdoc">base transformation</div><div class="ttdef"><b>Definition:</b> gicp.h:275</div></div>
<div class="ttc" id="aclasspcl_1_1_not_enough_points_exception_html"><div class="ttname"><a href="classpcl_1_1_not_enough_points_exception.html">pcl::NotEnoughPointsException</a></div><div class="ttdoc">An exception that is thrown when the number of correspondants is not equal to the minimum required</div><div class="ttdef"><b>Definition:</b> exceptions.h:66</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_a09c70d8e06e3fb4f07903fe6f8d67869"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#a09c70d8e06e3fb4f07903fe6f8d67869">pcl::PCLBase&lt; PointSource &gt;::input_</a></div><div class="ttdeci">PointCloudConstPtr input_</div><div class="ttdoc">The input point cloud dataset.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:150</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_base_html_aaee847c8a517ebf365bad2cb182a6626"><div class="ttname"><a href="classpcl_1_1_p_c_l_base.html#aaee847c8a517ebf365bad2cb182a6626">pcl::PCLBase&lt; PointSource &gt;::indices_</a></div><div class="ttdeci">IndicesPtr indices_</div><div class="ttdoc">A pointer to the vector of point indices to use.</div><div class="ttdef"><b>Definition:</b> pcl_base.h:153</div></div>
<div class="ttc" id="aclasspcl_1_1_p_c_l_exception_html"><div class="ttname"><a href="classpcl_1_1_p_c_l_exception.html">pcl::PCLException</a></div><div class="ttdoc">A base class for all pcl exceptions which inherits from std::runtime_error</div><div class="ttdef"><b>Definition:</b> exceptions.h:65</div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html"><div class="ttname"><a href="classpcl_1_1_point_cloud.html">pcl::PointCloud&lt; PointSource &gt;</a></div></div>
<div class="ttc" id="aclasspcl_1_1_point_cloud_html_af16a62638198313b9c093127c492c884"><div class="ttname"><a href="classpcl_1_1_point_cloud.html#af16a62638198313b9c093127c492c884">pcl::PointCloud::points</a></div><div class="ttdeci">std::vector&lt; PointT, Eigen::aligned_allocator&lt; PointT &gt; &gt; points</div><div class="ttdoc">The point data.</div><div class="ttdef"><b>Definition:</b> point_cloud.h:410</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a023e79a041ee70e8383654432cf5a71e"><div class="ttname"><a href="classpcl_1_1_registration.html#a023e79a041ee70e8383654432cf5a71e">pcl::Registration&lt; PointSource, PointTarget, float &gt;::final_transformation_</a></div><div class="ttdeci">Matrix4 final_transformation_</div><div class="ttdoc">The final transformation matrix estimated by the registration method after N iterations.</div><div class="ttdef"><b>Definition:</b> registration.h:505</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a15aa975f33a8f22573bad118ddda10dd"><div class="ttname"><a href="classpcl_1_1_registration.html#a15aa975f33a8f22573bad118ddda10dd">pcl::Registration&lt; PointSource, PointTarget, float &gt;::corr_dist_threshold_</a></div><div class="ttdeci">double corr_dist_threshold_</div><div class="ttdoc">The maximum distance threshold between two correspondent points in source &lt;-&gt; target....</div><div class="ttdef"><b>Definition:</b> registration.h:527</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a26eae6a42450893ca1c2ed81560159f2"><div class="ttname"><a href="classpcl_1_1_registration.html#a26eae6a42450893ca1c2ed81560159f2">pcl::Registration&lt; PointSource, PointTarget, float &gt;::getClassName</a></div><div class="ttdeci">const std::string &amp; getClassName() const</div><div class="ttdoc">Abstract class get name method.</div><div class="ttdef"><b>Definition:</b> registration.h:422</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a2cdeaab1c7d5e156a7bd35ee71c1f0db"><div class="ttname"><a href="classpcl_1_1_registration.html#a2cdeaab1c7d5e156a7bd35ee71c1f0db">pcl::Registration&lt; PointSource, PointTarget, float &gt;::transformation_</a></div><div class="ttdeci">Matrix4 transformation_</div><div class="ttdoc">The transformation matrix estimated by the registration method.</div><div class="ttdef"><b>Definition:</b> registration.h:508</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a3362d946f4b60e2628dc02e2af1f24fd"><div class="ttname"><a href="classpcl_1_1_registration.html#a3362d946f4b60e2628dc02e2af1f24fd">pcl::Registration&lt; PointSource, PointTarget, float &gt;::tree_reciprocal_</a></div><div class="ttdeci">KdTreeReciprocalPtr tree_reciprocal_</div><div class="ttdoc">A pointer to the spatial search object of the source.</div><div class="ttdef"><b>Definition:</b> registration.h:488</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a6957c3193d73098cb0535d6625d591d4"><div class="ttname"><a href="classpcl_1_1_registration.html#a6957c3193d73098cb0535d6625d591d4">pcl::Registration&lt; PointSource, PointTarget, float &gt;::nr_iterations_</a></div><div class="ttdeci">int nr_iterations_</div><div class="ttdoc">The number of iterations the internal optimization ran for (used internally).</div><div class="ttdef"><b>Definition:</b> registration.h:491</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a79b6170328705f29854aba00c4feb66d"><div class="ttname"><a href="classpcl_1_1_registration.html#a79b6170328705f29854aba00c4feb66d">pcl::Registration&lt; PointSource, PointTarget, float &gt;::tree_</a></div><div class="ttdeci">KdTreePtr tree_</div><div class="ttdoc">A pointer to the spatial search object.</div><div class="ttdef"><b>Definition:</b> registration.h:485</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a8d0064ba2f733ef07476f42de09a656f"><div class="ttname"><a href="classpcl_1_1_registration.html#a8d0064ba2f733ef07476f42de09a656f">pcl::Registration&lt; PointSource, PointTarget, float &gt;::previous_transformation_</a></div><div class="ttdeci">Matrix4 previous_transformation_</div><div class="ttdoc">The previous transformation matrix estimated by the registration method (used internally).</div><div class="ttdef"><b>Definition:</b> registration.h:511</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_a8e94793b677e107410ebb29ea2f931e9"><div class="ttname"><a href="classpcl_1_1_registration.html#a8e94793b677e107410ebb29ea2f931e9">pcl::Registration&lt; PointSource, PointTarget, float &gt;::converged_</a></div><div class="ttdeci">bool converged_</div><div class="ttdoc">Holds internal convergence state, given user parameters.</div><div class="ttdef"><b>Definition:</b> registration.h:536</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_aa776d097d20137f2702a275d931989d2"><div class="ttname"><a href="classpcl_1_1_registration.html#aa776d097d20137f2702a275d931989d2">pcl::Registration&lt; PointSource, PointTarget, float &gt;::max_iterations_</a></div><div class="ttdeci">int max_iterations_</div><div class="ttdoc">The maximum number of iterations the internal optimization should run for. The default value is 10.</div><div class="ttdef"><b>Definition:</b> registration.h:496</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_adbd6519634f433c0be2fd640c0c75108"><div class="ttname"><a href="classpcl_1_1_registration.html#adbd6519634f433c0be2fd640c0c75108">pcl::Registration&lt; PointSource, PointTarget, float &gt;::transformation_epsilon_</a></div><div class="ttdeci">double transformation_epsilon_</div><div class="ttdoc">The maximum difference between two consecutive transformations in order to consider convergence (user...</div><div class="ttdef"><b>Definition:</b> registration.h:516</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_ae210269f0404556b8dd7f4306084a91d"><div class="ttname"><a href="classpcl_1_1_registration.html#ae210269f0404556b8dd7f4306084a91d">pcl::Registration&lt; PointSource, PointTarget, float &gt;::initComputeReciprocal</a></div><div class="ttdeci">bool initComputeReciprocal()</div><div class="ttdoc">Internal computation when reciprocal lookup is needed</div><div class="ttdef"><b>Definition:</b> registration.hpp:102</div></div>
<div class="ttc" id="aclasspcl_1_1_registration_html_af9ac08a379a3b5db44c5c502cf6a882e"><div class="ttname"><a href="classpcl_1_1_registration.html#af9ac08a379a3b5db44c5c502cf6a882e">pcl::Registration&lt; PointSource, PointTarget, float &gt;::target_</a></div><div class="ttdeci">PointCloudTargetConstPtr target_</div><div class="ttdoc">The input point cloud dataset target.</div><div class="ttdef"><b>Definition:</b> registration.h:502</div></div>
<div class="ttc" id="aclasspcl_1_1_solver_didnt_converge_exception_html"><div class="ttname"><a href="classpcl_1_1_solver_didnt_converge_exception.html">pcl::SolverDidntConvergeException</a></div><div class="ttdoc">An exception that is thrown when the non linear solver didn't converge</div><div class="ttdef"><b>Definition:</b> exceptions.h:51</div></div>
<div class="ttc" id="aclasspcl_1_1search_1_1_kd_tree_html_a6be8fe286786c3b1aeda7d5369f9cb3e"><div class="ttname"><a href="classpcl_1_1search_1_1_kd_tree.html#a6be8fe286786c3b1aeda7d5369f9cb3e">pcl::search::KdTree::nearestKSearch</a></div><div class="ttdeci">int nearestKSearch(const PointT &amp;point, int k, std::vector&lt; int &gt; &amp;k_indices, std::vector&lt; float &gt; &amp;k_sqr_distances) const</div><div class="ttdoc">Search for the k-nearest neighbors for the given query point.</div><div class="ttdef"><b>Definition:</b> kdtree.hpp:88</div></div>
<div class="ttc" id="agroup__common_html_ga52d532f7f2b4d7bba78d13701d3a33d8"><div class="ttname"><a href="group__common.html#ga52d532f7f2b4d7bba78d13701d3a33d8">pcl::transformPointCloud</a></div><div class="ttdeci">void transformPointCloud(const pcl::PointCloud&lt; PointT &gt; &amp;cloud_in, pcl::PointCloud&lt; PointT &gt; &amp;cloud_out, const Eigen::Transform&lt; Scalar, 3, Eigen::Affine &gt; &amp;transform, bool copy_all_fields=true)</div><div class="ttdoc">Apply an affine transform defined by an Eigen Transform</div><div class="ttdef"><b>Definition:</b> transforms.hpp:42</div></div>
<div class="ttc" id="astructpcl_1_1_generalized_iterative_closest_point_1_1_optimization_functor_with_indices_html"><div class="ttname"><a href="structpcl_1_1_generalized_iterative_closest_point_1_1_optimization_functor_with_indices.html">pcl::GeneralizedIterativeClosestPoint::OptimizationFunctorWithIndices</a></div><div class="ttdoc">optimization functor structure</div><div class="ttdef"><b>Definition:</b> gicp.h:355</div></div>
<div class="ttc" id="astructpcl_1_1_point_x_y_z_r_g_b_a_html"><div class="ttname"><a href="structpcl_1_1_point_x_y_z_r_g_b_a.html">pcl::PointXYZRGBA</a></div><div class="ttdoc">A point structure representing Euclidean xyz coordinates, and the RGBA color.</div><div class="ttdef"><b>Definition:</b> point_types.hpp:540</div></div>
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